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作 者:董伟航 胡勇 田广军 郭晓磊 DONG Wei-hang;HU Yong;TIAN Guang-jun;GUO Xiao-lei(College of Materials Science and Engineering,Nanjing Forestry University,Nanjing Jiangsu 210037,China;Bosun Prewi(Shanghai)Tool System Co.,Ltd,Shanghai 201316,China)
机构地区:[1]南京林业大学材料科学与工程学院,江苏南京210037 [2]博深普锐高(上海)工具有限公司,上海201316
出 处:《林业机械与木工设备》2020年第10期4-8,共5页Forestry Machinery & Woodworking Equipment
基 金:江苏省研究生科研与实践创新计划项目(SJCX20_0273)。
摘 要:刀具智能化监测发展迅速,目前已有多种信号监测方式,选择合适的监测信号能够提高刀具磨损在线监测的精确度、优化产品加工质量、降低企业的生产成本。对加工时影响切削功率的主要因素、功率采集方法、信号处理方法与特征提取、监测模型进行综述,分析其关键技术,旨在加快木制品制造智能化进程,丰富木工刀具磨损在线监测理论。Recently,the intelligent monitoring of cutting tools has developed rapidly.A variety of signal monitoring methods have been adopted.Selecting appropriate cutter monitoring signals can improve the online monitoring accuracy of tool wear,optimize product processing quality and reduce production costs of enterprises.The overview of main factors affecting cutting power,cutting power collecting methods,signal processing methods,feature extraction,and monitoring models was conducted,with key technologies analyzed with the aim to accelerate the intelligent process of wood product manufacturing and enrich the online monitoring theories related to woodworking cutter wear.
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